The Seoul National University College of Engineering announced that a joint research team from Seoul National University and Harvard University has developed a next-generation, nature-inspired swarm robot system that can move, explore, transport, and cooperate without requiring precise sensors or central control.
The study was led by Professor Ho-Young Kim, Dr. Kyungmin Son, and Master's student Kwanwoo Kim at SNU's Department of Mechanical Engineering, and Professor L. Mahadevan and Dr. Kimberly Bowal at Harvard University. Their approach connects simple, active particles into chain-like structures that can perform complex tasks without advanced programming or artificial intelligence.
Conventional swarm robots—such as those composed of drones or small individual robots—typically rely on high-tech components like sophisticated sensors, wireless communication, and detailed control algorithms. While powerful, these systems often have limitations in terms of size, material selection, cost, and environmental conditions.
Nature, on the other hand, offers a different model. For example, ant colonies or cell clusters exhibit complex collective behaviors composed solely of simple individual units. The research team developed a new type of robot inspired by this phenomenon, known as 'emergent collective behavior.' Their solution, the Link-Bot, connects small, self-moving particles in a V-shaped chain formation, naturally enabling coordinated, lifelike movements—without embedded intelligence.
These Link-Bots use simple mechanical constraints to control the movement and rotation of each particle. By adjusting the geometry of the links, the system can adapt its shape and behavior to different tasks or environments.
The team demonstrated that Link-Bots can perform a variety of actions—such as moving forward, stopping, and changing direction—by simply adjusting their connection structures. They can squeeze through tight gaps, block openings, and even surround and carry objects. Multiple Link-Bots can also collaborate to tackle tasks that are too difficult for a single robot.
DOI
10.1126/sciadv.adu8326
